PHOSPHORUS LOADING REDUCTIONS NEEDED TO CONTROL BLUE-GREEN-ALGAL BLOOMS IN LAKE-MENDOTA

We evaluated the reductions in P loading needed to control blue-green algal blooms in Lake Mendota, Wisconsin. After developing a 21-year lo ading data set, we used a P mass balance model expressed as a differen ce equation with an annual time step indexed from mid-April. We define d and estimated a loss parameter lambda as the proportion of the lake' s April P concentration lost through sedimentation and outflow during the following year. Using the distribution of annual lambda's and inpu t loadings, we predicted the steady-state distribution of April P conc entrations that would result from scenarios of altered inputs due to c hanges in management practices. These results were then linked to the probability of summer blue-green algal blooms. For no load reduction, the probability of a bloom (>2 mg algae . L-1) on any summer day is ab out 60%. This probability decreases to 20% with a load reduction of 50 %. Our approach illustrates how managers can consider reducing the fre quency of extreme events like algal blooms, which may correspond more to the public's perception of lake water quality than average conditio ns.